Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, compar...

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Bibliographic Details
Published in:	Computer methods and programs in biomedicine Vol. 113; no. 3; pp. 736 - 748
Main Authors:	Martins, Maria, Costa, Lino, Frizera, Anselmo, Ceres, Ramón, Santos, Cristina
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ireland Ltd 01.03.2014 Elsevier
Subjects:	Adult Algorithms Applied sciences Biological and medical sciences Biomechanical Phenomena Computational Biology Computer science; control theory; systems Data processing. List processing. Character string processing Dependent Ambulation - physiology Dependent Ambulation - statistics & numerical data Diseases of the osteoarticular system. Orthopedic treatment Evolutionary algorithms Exact sciences and technology Gait - physiology Gait analysis Humans Internal Medicine Medical sciences Memory organisation. Data processing Models, Biological Other Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Rehabilitation - instrumentation Rehabilitation - statistics & numerical data Software Support Vector Machine Walker assistance Walkers Young Adult Walker assistance Gait analysis Evolutionary algorithms Space time correlation Gait Redundancy Evolutionary algorithm Handicapped aid Pedestrian Hybridization Posture Walking Pain Genetic algorithm Annoyance Kinematics Vector support machine Selection criterion Medical application
ISSN:	0169-2607, 1872-7565, 1872-7565
Online Access:	Get full text
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